{"id":"W2271206385","doi":"10.1561/2300000035","title":"A Review of Point Cloud Registration Algorithms for Mobile Robotics","year":2015,"lang":"en","type":"review","venue":"Foundations and Trends in Robotics","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":691,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; European Commission","keywords":"Robotics; Artificial intelligence; Computer science; Point cloud; Focus (optics); Point (geometry); Perspective (graphical); Image registration; Object (grammar); Computer vision; Mobile robot; Algorithm; Robot; Image (mathematics); Mathematics; Geometry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008820128,0.001397928,0.001556852,0.003914883,0.0005124012,0.001440666,0.001743141,0.001604341,0.006359661],"category_scores_gemma":[0.002633036,0.0009010758,0.00106622,0.005260236,0.0007268536,0.002930554,0.001097291,0.001554167,0.006445992],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006986177,"about_ca_system_score_gemma":0.001772028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001712176,"about_ca_topic_score_gemma":0.001641433,"domain_scores_codex":[0.9993063,0.0000914456,0.0001101825,0.0001625941,0.0002875347,0.00004184885],"domain_scores_gemma":[0.9988096,0.0005692545,0.0001116968,0.0000606449,0.0004124093,0.00003643491],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002988613,0.00004313633,0.0002128629,0.0146336,0.00006138613,0.000118443,0.00007900167,0.001716778,0.001890514,0.008464503,0.02402231,0.9487275],"study_design_scores_gemma":[0.000007232586,0.00009522521,0.0008331248,0.003997628,0.00009886909,0.001237593,0.00007797795,0.001342345,0.001432758,0.006444634,0.9843652,0.00006725768],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0004254944,0.9727648,0.01861604,0.000600401,0.0006463178,0.00004030096,0.0001405459,0.000144889,0.006621114],"genre_scores_gemma":[0.002926621,0.9771338,0.01608033,0.0004004654,0.0005816861,0.00005608905,0.0003208857,0.0000436466,0.002456475],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.006359661,"threshold_uncertainty_score":0.02127522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08526266431262461,"score_gpt":0.3636447742066176,"score_spread":0.278382109893993,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}